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Diffusion-Based Stress Testing of Overload Monitoring for Resilient Emergency Cellular Networks Using Internet CDR Proxies

arXiv:2610.04526v1 Announce Type: cross Abstract: Disasters can overload cellular control-plane signaling within minutes, yet fine-grained Radio Resource Control (RRC) or Next Generation (NG) Applicat

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Dimension-Free Decentralized Nonsmooth Nonconvex Stochastic Optimization

DGX agent

arXiv:2610.05789v1 Announce Type: cross Abstract: We investigate decentralized nonsmooth nonconvex stochastic optimization over a network of n nodes, with the goal of finding an (elta,epsilon)-Goldste

researcharxiv-cs-lg

6 Oct 2026

dIon: Fragmentation-Based Invariance for Self-Supervised Learning of Tandem Mass Spectra

arXiv:2610.06282v1 Announce Type: new Abstract: We introduce a novel invariance for peptide tandem mass spectrometry data, unlocking self-supervised representation learning that improves de novo seque

Discrete Action Matching: Learning Stochastic Dynamics from Samples via State Graphs

arXiv:2610.05071v1 Announce Type: new Abstract: Learning population dynamics from unpaired temporal marginals is an ill-posed inverse problem that requires structural assumptions on the underlying dyn

Distributed Cascade Force Control of Soft-Tactile-Based Multi-robot System for Object Transportation

arXiv:2610.04775v1 Announce Type: new Abstract: In this paper, we present a distributed cascade force control system (DCFC) for multiple robots with the aim of pushing a rigid object towards a desired

Distribution Matching Evolutionary Algorithms for Rare Event Sampling

arXiv:2610.03833v1 Announce Type: cross Abstract: A novel discovery is one which is both useful and surprising: a generative model's output is a useful discovery if it has a low probability of being g

Divide-and-Conquer CoT: RL for Reducing Latency via Parallel Reasoning

arXiv:2601.23027v2 Announce Type: replace Abstract: Long chain-of-thought reasoning (Long CoT) is now fundamental to state-of-the-art LLMs, especially in mathematical reasoning. However, LLM generatio

Do RUL explanations hold up? Faithfulness and stability of attributions on C-MAPSS

arXiv:2610.04278v1 Announce Type: new Abstract: Deep remaining-useful-life (RUL) models on NASA C-MAPSS are now routine, and so are heatmaps that colour sensors and timesteps. A heatmap that looks mec

DynaMesh: Dynamic 3D Texture Generation

arXiv:2610.05529v1 Announce Type: new Abstract: We present DynaMesh, a dynamic texture generation method for 3D meshes. Given a textureless shape and a text prompt describing an effect, our method pro

Dynamic Minimax Regret Optimization for Robust LLM Post-Training

arXiv:2610.06329v1 Announce Type: new Abstract: Modern LLM training increasingly relies on heterogeneous data sources spanning different domains, tasks, preference distributions, and difficulty levels

Dynamic Time Step Prediction in Inverse Heat Dissipation for Blur-Like Image Restoration Tasks

arXiv:2610.03942v1 Announce Type: new Abstract: When using diffusion models to target image restoration problems, diffusion inversion is typically employed to retain relevant image information from th

DyQ-VLA: Temporal-Dynamic-Aware Quantization for Embodied Vision-Language-Action Models

arXiv:2603.07904v3 Announce Type: replace Abstract: Vision-language-action (VLA) models achieve favorable task performance, yet runtime errors in closed-loop execution evolve with alternating updates

EagleDepth: Efficient Fine-Grained Depth Estimation via Pixel Diffusion Decoder

arXiv:2610.04554v1 Announce Type: new Abstract: Recovering detailed geometry from high-resolution images is critical for precise perception of the surroundings and objects. However, existing methods w

EEGDM: Label-Efficient EEG Representation Learning with Generative Diffusion Model

arXiv:2508.14086v4 Announce Type: replace Abstract: Electroencephalography (EEG) is a critical tool for monitoring brain activity and diagnosing neurological disorders such as epilepsy. However, learn

Efficient Hierarchical Transformers for Representing Log Data

arXiv:2408.16803v2 Announce Type: replace Abstract: Transformers have gained widespread acclaim for their versatility in handling diverse data structures, yet their application to log data remains und

Emergency Obstacle Avoidance Maneuvers in Differential-Drive Mobile Robots

arXiv:2610.05607v1 Announce Type: new Abstract: Emergency obstacle avoidance requires a mobile robot to brake or change its heading within the available distance. This paper investigates the dependenc

Emergent Underactuation in Fully Actuated Multirotors by Minimizing a Homogeneous Allocation Cost

arXiv:2610.04726v1 Announce Type: new Abstract: Full actuation is commonly valued for independent position and attitude tracking. This work establishes a complementary principle: when only a position

EMG-GPT: Predictive Pretraining on Residual-Quantized EMG Tokens for Hand Pose Estimation

arXiv:2610.05235v1 Announce Type: new Abstract: Surface electromyography (sEMG) is a low-power, cost-effective biosignal for hand-pose estimation and gesture classification. In this work, we examine w

Empirical Variational Autoencoder

arXiv:2610.06545v1 Announce Type: new Abstract: We present Empirical Variational Autoencoder, a general generative framework for continuous-valued (i.e., non-vector-quantized) sequences. EVA is based

EndoWave: 4D Gaussian Splatting with Rational Wavelet for Endoscopic Reconstruction

arXiv:2510.23087v2 Announce Type: replace Abstract: In robot-assisted minimally invasive surgery, accurate 3D reconstruction from endoscopic video is vital for downstream tasks and improved outcomes.

EpicWorldModel: Exploration-driven Planning with Latent World Models

arXiv:2610.05996v1 Announce Type: new Abstract: Latent world models based on Joint-Embedding Predictive Architecture (JEPA) are deterministic by design. While successful in fully observable scenarios,

Evaluating Zone-Guided Front Extraction for Glacier Calving-Front Delineation in SAR Imagery

arXiv:2610.04066v1 Announce Type: new Abstract: Automatic calving-front delineation from synthetic aperture radar imagery is challenging because the front is a thin and often ambiguous boundary betwee

Event-based Continuous Color Video Decompression from Single Frames

arXiv:2312.00113v4 Announce Type: replace Abstract: We present ContinuityCam, a novel approach to generate a continuous video from a single static RGB image and an event camera stream. Conventional ca

Evolutionary feature selection for spiking neural network pattern classifiers

arXiv:2604.26654v1 Announce Type: cross Abstract: This paper presents an application of the biologically realistic JASTAP neural network model to classification tasks. The JASTAP neural network model

Exact Fast Batch Simulation for Tabular Reinforcement Learning

arXiv:2610.04746v1 Announce Type: cross Abstract: Simulation is a fundamental computational primitive in reinforcement learning (RL), yet conventional simulation explicitly generates individual trajec

Exact Optimal Transport by Matching

arXiv:2610.04085v1 Announce Type: cross Abstract: Balanced discrete optimal transport between n sources and n targets of unit mass is exactly the minimum-cost assignment problem-a bipartite perfect ma

F^2 SLAM: Turning Feed-Forward Geometry into Persistent Factors for SLAM

arXiv:2610.05207v1 Announce Type: new Abstract: Feed-forward 3D models provide strong multi-view geometric priors, while on- line simultaneous localization and mapping (SLAM) relies mainly on local me

Fast Convergence through Distributed Augmentation for Class-Imbalanced Federated Learning

arXiv:2610.05279v1 Announce Type: new Abstract: In federated learning, mitigating class imbalance is essential to improve minority-class performance. A common approach to address this problem is to au

FASTER: Fast Adjoint Stochastic Transport for Endpoint Refinement in Reward-Guided Image Editing

arXiv:2610.04538v1 Announce Type: new Abstract: Reward-guided image editing at test time seeks to improve a specified reward while preserving source content and visual plausibility. Many existing appr

Finding Gaussian Structure in Bosonic States

arXiv:2610.06810v1 Announce Type: cross Abstract: We study agnostic tomography of pure bosonic Gaussian states: given copies of an arbitrary n-mode bosonic state rho, the goal is to output a pure Gaus

FlexCast: Adaptive Weather Forecasting from Arbitrary Field Sets

arXiv:2610.05296v1 Announce Type: new Abstract: Most deep learning weather models assign a fixed set of variables and pressure levels to predefined channels, limiting transfer across atmospheric field

FloVMos: Optical Flow-based Medical Video Mosaicking

arXiv:2610.04258v1 Announce Type: cross Abstract: Biomedical imaging modalities often require a trade-off among resolution, field of view (FOV), and acquisition speed. Video mosaicking offers a strate

fMRI-TAMCL: Text-Anchored Supervised Multimodal Contrastive Learning for fMRI-Based Brain Disorder Classification

arXiv:2610.05880v1 Announce Type: new Abstract: Resting-state fMRI is important in the classification of brain disorders, but highly multimodal and exhibits strong multisite heterogeneity. Existing me

FoMo: A Multi-Season Dataset for Robot Navigation in Foret Montmorency

arXiv:2603.08433v2 Announce Type: replace Abstract: The Foret Montmorency (FoMo) dataset is a comprehensive multi-season data collection, recorded over the span of one year in a boreal forest. Featuri

Fractal Cross Product: Theory, Differentiable Implementation and Application to Medical Image Analysis

arXiv:2610.03755v1 Announce Type: new Abstract: The magnitude of the generalized Euclidean cross product is a Gram volume whose degree under common scaling is fixed by the integer dimension of the spa

FrontVeg V2: A Training-Free Software Framework for Foreground-Aware Zero-Shot Plant Trait Segmentation in High-Resolution Images of Trellised Crops

arXiv:2610.06575v1 Announce Type: new Abstract: FrontVeg V2 is an open-source, training-free software framework for foregroundaware zero-shot segmentation of plant traits in high-resolution images of

Game Plan: What AI can do for Football, and What Football can do for AI

arXiv:2011.09192v1 Announce Type: cross Abstract: The rapid progress in artificial intelligence (AI) and machine learning has opened unprecedented analytics possibilities in various team and individua

Gauss-Map Variation for Image Denoising: Geometric Analysis and an Anderson--Accelerated Majorization--Minimization Method

arXiv:2610.05801v1 Announce Type: new Abstract: We propose a Gauss-map variation (GMV) model for image denoising that measures the spatial variation of the tangent-plane projectors of the scaled image

Generalizable Neural Downscaling of Earth System Model Wind Fields via Continuous Dynamics Modeling

arXiv:2610.03757v1 Announce Type: cross Abstract: Accurate high-resolution wind field simulations are critical for resolving fine-scale atmospheric dynamics, yet the simulation of wind fields in Earth

GeoBridge-VLA: Geometry-Aware Residual Adaptation for Vision-Language-Action Models

arXiv:2610.05026v1 Announce Type: new Abstract: Vision-language-action (VLA) models encode semantic information from vision-language pretraining, but manipulation also requires precise spatial reasoni

GFPack++: Attention-Driven Gradient Fields for Optimizing 2D Irregular Packing

arXiv:2406.07579v2 Announce Type: replace-cross Abstract: 2D irregular packing is a classic combinatorial optimization problem with various applications, such as material utilization and texture atlas

Global Communication or Graph-Specific Memory?

arXiv:2610.05874v1 Announce Type: new Abstract: Scalable Graph Transformers are commonly trained and evaluated on static large graphs in a transductive setup. Many scalable Graph Transformer component

GO-Based Clustering for Learning Cluster-Level Causal Gene Regulatory Networks

arXiv:2610.06042v1 Announce Type: new Abstract: Discovery of causal relationships in high-dimensional Gene Regulatory Networks (GRN) is computationally challenging and often difficult to interpret due

Grad-CAM for Visualizing Attention Regions of PCA and SVM Layers in Convolutional Neural Networks

arXiv:2508.11880v2 Announce Type: replace Abstract: Convolutional Neural Networks (CNNs) are an effective approach for classification tasks, particularly when the training dataset is large. Although C

Gradient descent dynamics for deep equilibrium models

arXiv:2511.16976v3 Announce Type: replace Abstract: Deep equilibrium models (DEQs) have recently emerged as a powerful paradigm for training infinitely deep weight-tied neural networks that achieve st

Gradient-Free Sampling from Generative Models via Stochastic Bounded Extremum Seeking

arXiv:2610.04568v1 Announce Type: cross Abstract: We introduce a sampling approach for energy- and score-based generative models that requires no gradient evaluations of the model. Replacing the drift

GS-Pool: Object-Level Change Detection in 3D Gaussian Splatting

arXiv:2610.06688v1 Announce Type: new Abstract: Factories, museums and surveyors photograph the same space months apart and need to know which objects changed. When each visit is reconstructed with 3D

H-JEPA: End-to-End Learning of Hierarchical World Models for Visual Planning

arXiv:2610.06805v1 Announce Type: new Abstract: Long-horizon planning with latent world models requires reasoning across timescales and levels of abstraction. Existing task-agnostic JEPA world models